Warehousing Tweets and Stock Data

Project Goals

This project aims to build a simple data warehouse in SQLite for a sample of tweets and stock data sourced from Kaggle. The data warehouse will aggregate monthly twitter mentions and volume weighted average opening and closing price

Data Source

• Stock Tweets for Sentiment Analysis and Prediction - HANNA YUKHYMENKO
• https://www.kaggle.com/datasets/equinxx/stock-tweets-for-sentiment-analysis-and-prediction?select=stock_yfinance_data.csv

Key Calculations

• Volume Weighted Average Price (VWAP):
  • $VWAP = \frac{\sum{Volume\ \cdot\ Price}}{\sum{Volume}}$
• Price:
  • $Price = \frac{(High\ +\ Low+\ Close)}{3}$
• https://education.howthemarketworks.com/volume-weighted-average-price/

Conclusion

Successfully created data warehouse file and met requirements. Takeaways and ideas:

• Add other stock metrics to fact table such as return data or volatility measures
• Adapt into a general SQL file for other databases
• Clean dim tables and add new external attributes like metadata or more company information
• Conform load tables to schema ERD